Senior Data Engineer
We’re looking for a Senior Data Engineer with deep, hands-on Databricks experience to be a key technical reference for the team. This is a senior individual contributor role. You have built and run production lakehouse pipelines, dealt with complex data governance challenges and solved hard architecture problems. You’ll bring that experience through design reviews, code feedback and day-to-day technical guidance, working in an Agile/sprint model with distributed teams. Responsibilities
• Design, build and maintain scalable batch and streaming pipelines with Databricks, Lakeflow Declarative Pipelines and dbt.
• Take part in Agile ceremonies (planning, standups, retros, grooming) and deliver in iterative sprints.
• Optimize, monitor and troubleshoot pipeline reliability, cost and performance using Photon, Liquid Clustering and Serverless compute.
• Implement centralized data governance and access control with Unity Catalog and third-party tools such as Immuta.
• Set DataOps standards and CI/CD automation with Declarative Automation Bundles (DABs) and automated data quality checks.
• Work with cross-functional stakeholders to deliver curated, analytics-ready data models.
• Mentor mid-level and junior engineers through design reviews and substantive code feedback.
• Evaluate new Databricks capabilities (Lakeflow, AI/BI, SQL AI Functions) and recommend improvements to the platform. Must have
• 7+ years in data engineering and architecture,
focused on lakehouse and big data platforms at production scale.
• Strong production experience with Databricks, Apache Spark (PySpark/Spark SQL) and declarative pipelines.
• Experience with dbt, Databricks Workflows and Apache Airflow.
• Advanced SQL and strong Python.
• Solid understanding of lakehouse architecture, medallion modeling and data warehousing.
• Production experience with Unity Catalog and at least one cloud: GCP, Azure or AWS.
• Experience working in Agile/Scrum with distributed teams.
• Strong communication skills and advanced English. Nice to have
• Kafka (Confluent), Fivetran, Google Pub/Sub.
• Alation or similar catalog and lineage tools.
• Immuta alongside Unity Catalog security.
• Data contracts, data mesh and data product thinking.
• Lakebase for operational and OLTP workloads.
• GCP: BigQuery, GCS, Pub/Sub.
• SQL Server, Oracle, PostgreSQL; Power BI, Palantir.
• ML/AI workflows, Feature Store, Databricks AI/BI, GenAI or agentic tooling in data workflows.
• Scala or Java.
• Databricks Certified Data Engineer Professional (strong plus) and GCP, Azure or Power BI certifications. This job opening includes people registered in the National Registry for Persons with Disabilities (Registro Nacional de Personas con Discapacidad
- Ley N° 19.691) who meet the conditions and suitability for the position. If you require any accommodations during the application process, please reach out to us at (email hidden).
• Design, build and maintain scalable batch and streaming pipelines with Databricks, Lakeflow Declarative Pipelines and dbt.
• Take part in Agile ceremonies (planning, standups, retros, grooming) and deliver in iterative sprints.
• Optimize, monitor and troubleshoot pipeline reliability, cost and performance using Photon, Liquid Clustering and Serverless compute.
• Implement centralized data governance and access control with Unity Catalog and third-party tools such as Immuta.
• Set DataOps standards and CI/CD automation with Declarative Automation Bundles (DABs) and automated data quality checks.
• Work with cross-functional stakeholders to deliver curated, analytics-ready data models.
• Mentor mid-level and junior engineers through design reviews and substantive code feedback.
• Evaluate new Databricks capabilities (Lakeflow, AI/BI, SQL AI Functions) and recommend improvements to the platform. Must have
• 7+ years in data engineering and architecture,
focused on lakehouse and big data platforms at production scale.
• Strong production experience with Databricks, Apache Spark (PySpark/Spark SQL) and declarative pipelines.
• Experience with dbt, Databricks Workflows and Apache Airflow.
• Advanced SQL and strong Python.
• Solid understanding of lakehouse architecture, medallion modeling and data warehousing.
• Production experience with Unity Catalog and at least one cloud: GCP, Azure or AWS.
• Experience working in Agile/Scrum with distributed teams.
• Strong communication skills and advanced English. Nice to have
• Kafka (Confluent), Fivetran, Google Pub/Sub.
• Alation or similar catalog and lineage tools.
• Immuta alongside Unity Catalog security.
• Data contracts, data mesh and data product thinking.
• Lakebase for operational and OLTP workloads.
• GCP: BigQuery, GCS, Pub/Sub.
• SQL Server, Oracle, PostgreSQL; Power BI, Palantir.
• ML/AI workflows, Feature Store, Databricks AI/BI, GenAI or agentic tooling in data workflows.
• Scala or Java.
• Databricks Certified Data Engineer Professional (strong plus) and GCP, Azure or Power BI certifications. This job opening includes people registered in the National Registry for Persons with Disabilities (Registro Nacional de Personas con Discapacidad
- Ley N° 19.691) who meet the conditions and suitability for the position. If you require any accommodations during the application process, please reach out to us at (email hidden).